1. Field of the Invention
The present invention relates to signal processing equalizers, and, more specifically, to tap coefficient calculations for such devices.
2. Description of the Related Art
FIG. 1 shows a block diagram of one implementation of a prior-art chip-rate receiver 100. Receiver 100 has upstream processing 102, chip-rate normalized-least-mean-squares (NLMS) equalizer 104, and downstream processing 106. Upstream processing 102 performs pre-equalization processing which might include analog-to-digital conversion, root-raised-cosine filtering, or other processing to prepare a received signal for equalization. NLMS equalizer 104 receives digital data y(i) from upstream processing 102, equalizes signal y(i) to closely approximate the originally transmitted signal, and outputs equalized signal {circumflex over (x)}(i) to downstream processing 106. Downstream processing 106 then performs post-equalization processing, which might include de-scrambling, de-spreading, symbol estimation, data symbol de-mapping, or other post-equalization processing for recovering one or more output data streams from the received signal.
NLMS equalizer 104 equalizes digital signal y(i) using an update loop that comprises finite impulse response (FIR) filter 108, coefficient updater 110, and error calculator 112. During each iteration of the update loop, FIR filter 108 receives a chip of signal y(i), where the number of samples per chip is equal to M. Additionally, FIR filter 108 receives a set of coefficients, where each coefficient w(i,t) corresponds to a tap t of FIR filter 108. Note that FIR filter 108 has a length of Tchips, and therefore, has a number of taps t equal to T×M. Furthermore, since each coefficient w(i,t) corresponds to a tap t, the coefficients range from w(i, 1), . . . , w(i, T×M). Each tap t multiplies a sample of signal y(i) by the corresponding coefficient w(i,t). The tap outputs are summed to form a chip of equalized signal {circumflex over (x)}(i). After each iteration of the update loop, FIR filter 108 outputs equalized signal {circumflex over (x)}(i) to downstream processing 106 and error calculator 112.
Error calculator 112 calculates error e(i) of equalized signal {circumflex over (x)}(i) during each iteration of the update loop by comparing signal {circumflex over (x)}(i) to an expected value z(i). In conventional transmissions, expected value z(i) is a pilot signal that is known to the receiver. As the difference between expected value z(i) and equalized signal {circumflex over (x)}(i) decreases, equalized output {circumflex over (x)}(i) more closely approximates the originally transmitted signal. Error signal e(i) is then output to coefficient updater 110.
Coefficient updater 110 calculates a new set of coefficients w(i,t) during each iteration of the update loop based on received signal y(i) and error signal e(i). As an example of the generation of coefficients w(i,t), assume that the length T of FIR filter 108 is equal to 4 and that the number M of samples per chip is equal to 1 (i.e., T×M=4). The generation of coefficients w(i,t) in this example is shown in Table I of FIG. 2. As shown, coefficient updater 110 does not begin generating coefficients w(i,t) until each position corresponding to a tap t of FIR filter 108 is matched with a sample Si. Once this occurs, coefficient updater 110 generates coefficients w(4,4), w(4,3), w(4,2), and w(4,1), which correspond to samples S4, S3, S2, and S1, respectively. After one chip of signal y(i) (i.e., an iteration), coefficient updater 110 generates new coefficients w(5,4), w(5,3), w(5,2), and w(5,1), which correspond to samples S5, S4, S3, and S2, respectively. This process continues for each subsequent chip of signal y(i).
Coefficients w(i,t) are calculated using an NLMS algorithm that employs a step size Δ to gradually step the error of each sample of y(i) toward a minimum value of the mean squared error (MSE). In relatively high-speed mobile environments (e.g., where the mobile station is traveling at speeds greater than 30 km/h), step size A should be chosen so that NLMS equalizer 104 can adapt quickly to channel changes (e.g., fast fading). Thus, as the speed of the mobile environment increases, step size Δ should be increased to allow for quicker tracking of the channel. However, as step size Δ is increased, NLMS equalizer 104 can overestimate the MSE. This overestimation induces adaptation noise in the coefficient calculations, which reduces the accuracy of coefficients w(i,t), which in turn can lead to errors in downstream processing 106.